- http://wiki.postgresql.org/wiki/Performance_Optimization - run it on the most powerful machine you can find - get some more memory - get a big (512-1TB) SSD drive - avoid recalculating the same things over and over. if your views have many similar elements, then calculate those first into a partial result, then build the final views from the partial result. - make sure your source tables are fully indexed and have good statistics - run all the views once with \timing and keep track of how long they took. Fix the slow ones. G On 07 Apr 2014, at 15:56, Nicolas Paris <niparisco@xxxxxxxxx> wrote: > Excellent. > > Maybe the last sub-question : > > Those 3600 mat views do have indexes. > I guess I will get better performances in dropping indexes first, then refresh, then re-creating indexes. > > Are there other way to improve performances (like mat views storage parameters), because this routines will be at night, and need to be finished quickly. > > Thanks > > Nicolas PARIS > > > 2014-04-07 14:59 GMT+02:00 Graeme B. Bell <grb@xxxxxxxxxxxxxxxxx>: > > Hi again Nick. > > Glad it helped. > > Generally, I would expect that doing all the A's first, then all the B's, and so on, would be fastest since you can re-use the data from cache. > > Concurrency when reading isn't generally a problem. Lots of things can read at the same time and it will be nice and fast. > It's concurrent writes or concurrent read/write of the same data item that causes problems with locking. That shouldn't be happening here, judging by your description. > > If possible, try to make sure nothing is modifying those source tables A/B/C/D/E/F when you are doing your view refresh. > > Graeme. > > On 07 Apr 2014, at 14:49, Nicolas Paris <niparisco@xxxxxxxxx> wrote: > > > Hello, > > Thanks for this clear explanation ! > > > > Then I have a sub-question : > > Supposed I have 3600 materialised views say 600 mat views from 6 main table. (A,B,C,D,E,F are repetead 600 times with some differences) > > Is it faster to : > > 1) parallel refresh 600 time A, then 600 time B etc, > > OR > > 2) parallel refresh 600 time A,B,C,D,E,F > > > > I guess 1) is faster because they are 600 access to same table loaded in memory ? But do parallel access to the same table implies concurency > > and bad performance ? > > > > Thanks > > > > Nicolas PARIS > > > > > > 2014-04-07 12:29 GMT+02:00 Graeme B. Bell <grb@xxxxxxxxxxxxxxxxx>: > > On 04 Apr 2014, at 18:29, Nicolas Paris <niparisco@xxxxxxxxx> wrote: > > > > > Hello, > > > > > > My question is about multiprocess and materialized View. > > > http://www.postgresql.org/docs/9.3/static/sql-creatematerializedview.html > > > I (will) have something like 3600 materialised views, and I would like to know the way to refresh them in a multithread way > > > (anderstand 8 cpu cores -> 8 refresh process in the same time) > > > > Hi Nick, > > > > out of DB solution: > > > > 1. Produce a text file which contains the 3600 refresh commands you want to run in parallel. You can do that with select and format() if you don't have a list already. > > > > 2. I'm going to simulate your 3600 'refresh' commands here with some select and sleep statements that finish at unknown times. > > > > (In BASH): > > for i in {1..3600} ; do echo "echo \"select pg_sleep(1+random()::int*10); select $i\" | psql mydb" ; done > 3600commands > > > > 3. Install Gnu Parallel and type: > > > > parallel < 3600commands > > > > 4. Parallel will automatically work out the appropriate number of cores/threads for your CPUs, or you can control it manually with -j. > > It will also give you a live progress report if you use --progress. > > e.g. this command balances 8 jobs at a time, prints a dynamic progress report and dumps stdout to /dev/null > > > > parallel -j 8 --progress < 3600commands > /dev/null > > > > 5. If you want to make debugging easier use the parameter --tag to tag output for each command. > > > > Of course it would be much more elegant if someone implemented something like Gnu Parallel inside postgres or psql ... :-) > > > > Hope this helps & have a nice day, > > > > Graeme. > > > > > > > > > > > > > > -- Sent via pgsql-performance mailing list (pgsql-performance@xxxxxxxxxxxxxx) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
